An Efficient Tasks Scheduling Algorithm for Drone Operations in the Indoor Environment

Abstract

The trend of drone applications in recent years has begun to change. The application of Drone or UAV (Unmanned Vehicle) brings flexibility in those areas that are difficult to reach or manage. The use of drones enables the structure of a semi-autonomous system, where workers in the performance of many tasks can be replaced by drones, affecting time savings and flexibility at work. This research proposes an efficient algorithm that can be applied to drones to transport materials into the indoor environment. This algorithm optimizes the time and reduces power consumption when sharing and completing tasks between different drones. In this research, the results will be achieved based on the "Earliest Time Algorithm". We have modified this algorithm, where we have managed to get much better results in terms of saving time while performing various tasks from the drone. It achieves by changing the logic of the impact of weight on the lifetime of the drone battery from linear to dynamic. Also, we have implemented the possibility of a partial charge of the drone battery. The experiments are performed in a test environment for various tasks performed by the drone. In this case, the impact of weight on algorithm performance as well as the impact of partial charging on time optimization in performing various tasks from the drone will be tested. The performance of the algorithm is tested and analyzed for three different types of drone tasks depending on the weight the drone carries. The results achieved with our algorithm are compared with the results of the existing algorithm.